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Water clarity response to climate warming and wetting of the Inner Mongolia-Xinjiang Plateau: A remote sensing approach

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  • Yibo Zhang, CAS - Nanjing Institute of Geography and Limnology, University of Chinese Academy of Sciences
  • ,
  • Kun Shi, CAS - Nanjing Institute of Geography and Limnology, University of Chinese Academy of Sciences, CAS Center for Excellence in Tibetan Plateau Earth Sciences
  • ,
  • Yunlin Zhang, CAS - Nanjing Institute of Geography and Limnology, University of Chinese Academy of Sciences
  • ,
  • Max Jacobo Moreno-Madriñán, Indiana University - Purdue University Indianapolis
  • ,
  • Xuan Xu, CAS - Nanjing Institute of Geography and Limnology
  • ,
  • Yongqiang Zhou, CAS - Nanjing Institute of Geography and Limnology, University of Chinese Academy of Sciences
  • ,
  • Boqiang Qin, CAS - Nanjing Institute of Geography and Limnology, University of Chinese Academy of Sciences
  • ,
  • Guangwei Zhu, CAS - Nanjing Institute of Geography and Limnology, University of Chinese Academy of Sciences
  • ,
  • Erik Jeppesen

Water clarity (generally quantified as the Secchi disk depth: SDD) is a key variable for assessing environmental changes in lakes. Using remote sensing we calculated and elucidated the SDD dynamics in lakes in the Inner Mongolia-Xinjiang Lake Zone (IMXL) from 1986 to 2018 in response to variations in temperature, rainfall, lake area, normalized difference vegetation index (NDVI) and Palmer's drought severity index (PDSI). The results showed that the lakes with high SDD values are primarily located in the Xinjiang region at longitudes of 75°–93° E. In contrast, the lakes in Inner Mongolia at longitudes of 93°–118° E generally have low SDD values. In total, 205 lakes show significant increasing SDD trends (P < 0.05), with a mean rate of 0.15 m per decade. In contrast, 75 lakes, most of which are located in Inner Mongolia, exhibited significant decreasing trends with a mean rate of 0.08 m per decade (P < 0.05). Pooled together, an overall increase is found with a mean rate of 0.14 m per decade. Multiple linear regression reveals that among the five variables selected to explain the variations in SDD, lake area accounts for the highest proportion of variance (25%), while temperature and rainfall account for 12% and 10%, respectively. In addition, rainfall accounts for 52% of the variation in humidity, 8% of the variation in lake area and 7% of the variation in NDVI. Temperature accounts for 27% of the variation in NDVI, 39% of the variation in lake area and 22% of the variation in PDSI. Warming and wetting conditions in IMXL thus promote the growth of vegetation and cause melting of glaciers and expansion of lake area, which eventually leads to improved water quality in the lakes in terms of higher SDD. In contrast, lakes facing more severe drought conditions, became more turbid.

OriginalsprogEngelsk
Artikelnummer148916
TidsskriftScience of the total Environment
Vol/bind796
ISSN0048-9697
DOI
StatusUdgivet - nov. 2021

Bibliografisk note

Funding Information:
This work was supported by the National Natural Science Foundation of China ( 41790423 , 41922005 , 42007160 and 41771472 ), the Youth Innovation Promotion Association (CAS) ( 2017365 ), and the Key Research Program of Frontier Sciences, Chinese Academy of Sciences ( QYZDB-SSW-DQC016 ). Erik Jeppesen was supported by WATEC (Centre for Water Technology, Aarhus University) and Tübitak BIDEB 2232 ( 118C250 ). We thank Anne Mette Poulsen from Aarhus University for editorial assistance and the United States Geological Survey (USGS) for providing all Landsat data. We would also like to thank Na Li and Xiao Sun for their help with field sample collection.

Publisher Copyright:
© 2021 Elsevier B.V.

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